The present invention generally relates to a way of optimizing fuel efficiency for an ensemble of generators being managed by a microgrid system. Currently, such systems may select a sub-set of generators that is able to power a particular aggregate load. Such determination may involve simply selecting the smallest generator that is able to supply the given load, or operating multiple generators in a less-than-optimal configuration. However, such a determination may not provide the most efficient solution in a system where multiple generators are required (and/or where multiple generators may be operated continuously regardless of actual loading conditions).
In addition, current microgrid systems may not recognize and adjust to real-time parameters (e.g., environmental conditions, subsystem maintenance levels, operational imperatives, etc.) and thus may have sub-optimal performance induced by internal and external variations.
Moreover, current microgrid systems may require extensive setup (including configuration and tuning) by experienced personnel. This requirement for microgrid initialization and/or calibration can be accomplished in a much timelier and more cost effective manner.
As can be seen, there is a need for an adaptable microgrid power management feature that optimizes fuel efficiency. In addition, there is a need for a self-configuring, auto-tuning grid requiring minimal manual inputs/oversight.
In one aspect of the present invention, a system designed to optimize fuel efficiency of a microgrid includes a set of controllable generators intended to supply power to the local grid, each generator in the set being associated with an embedded controller, a set of loads powered from the grid, and a microgrid supervisory controller designed to analyze and control generator engine torques on a system wide basis, based at least partly on microgrid monitored system loading.
In another aspect of the present invention, a method of optimizing fuel efficiency for a microgrid system includes determining the set of available generators and their performance characteristics, determining current system load conditions, computing all possible load partitions between generators, based at least partly on the set of available generators and based at least partly on system load conditions, each possible load partitioning solution being associated with a total fuel consumption, and identifying a load partition between generators with a minimum total fuel consumption from among all possible load partition solutions.
Another aspect of the present invention utilizes the development (and maintenance) of generator performance characterizations (models), the most important being a given unit's fuel efficiency as a function of load. The method includes incorporating characteristics provided by the generator manufacturer; characterizations performed during microgrid setup and calibration, and automated updates to system data sets based on continuous performance monitoring and data collection.
These and other features, aspects and advantages of the present invention will become better understood with reference to the following drawings, description and claims.